Velocity calculation device, velocity calculation method, and navigation device

ABSTRACT

A velocity calculation device includes: a vertical direction acceleration detection portion that is mounted on a vehicle and detects an acceleration in a vertical direction generated correspondingly to undulation of a road surface; a horizontal direction angular velocity detection portion that is mounted on the vehicle and detects an angular velocity about a horizontal axis orthogonal to a travel direction of the vehicle generated correspondingly to the undulation of the road surface; and a velocity calculation portion that calculates a velocity in the travel direction of the vehicle on the basis of the acceleration in the vertical direction and the angular velocity about the horizontal axis.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application is a continuation of U.S. application Ser. No.14/630,816, filed on Feb. 25, 2015, which is a continuation of U.S.application Ser. No. 12/583,666, filed on Aug. 24, 2009, now U.S. Pat.No. 8,989,982, which claims the benefit of Japanese Patent No.P2008-221713, filed on Aug. 29, 2008, the disclosures of which areincorporated herein by reference.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention relates to a velocity calculation device, avelocity calculation method, and a navigation device suitably applied,for example, to a portable navigation device.

2. Description of Related Art

A navigation device in the related art is configured to receivepositioning signals (hereinafter, referred to also as GPS signals) froma plurality of GPS (Global Positioning System) satellites and tocalculate a current position of the vehicle on the basis of the GPSsignals.

The navigation device as above, however, fails to receive GPS signalsfrom the GPS satellites when the vehicle on which is mounted thenavigation device goes, for example, into a tunnel or an undergroundparking and thereby becomes unable to calculate a current position ofthe vehicle on the basis of the GPS signals.

To avoid such an inconvenience, there is a type of navigation deviceconfigured to calculate a velocity in the travel direction on the basisof the acceleration in the horizontal direction orthogonal to the traveldirection of the vehicle and an angular velocity about the vertical axisorthogonal to the travel direction at the time of cornering, and tocalculate a current position on the basis of the velocity in the traveldirection even in a case where the navigation device fails to receivethe GPS signals. An example of such a navigation device is disclosed inJP-A-2008-76389.

SUMMARY OF THE INVENTION

The navigation device as described above is able to calculate thevelocity in the travel direction at the time of cornering but it isunable to calculate the velocity in the travel direction at the time ofstraight-ahead driving. The navigation device therefore has a problemthat the velocity in the travel direction is not necessarily calculatedin all the road environments.

Thus, it is desirable to provide a velocity calculation device, avelocity calculation method, and a navigation device capable ofcalculating the velocity of the vehicle at high accuracy in all the roadenvironments under any circumstance.

According to an embodiment of the present invention, there is provided avelocity calculation device including: a vertical direction accelerationdetection portion that is mounted on a vehicle and detects anacceleration in a vertical direction generated correspondingly toundulation of a road surface; a horizontal direction angular velocitydetection portion that is mounted on the vehicle and detects an angularvelocity about a horizontal axis orthogonal to a travel direction of thevehicle generated correspondingly to the undulation of the road surface;and a velocity calculation portion that calculates a velocity in thetravel direction of the vehicle on the basis of the acceleration in thevertical direction and the angular velocity about the horizontal axis.

According to another embodiment of the present invention, there isprovided a velocity calculation method including the steps of: detectingan acceleration in a vertical direction generated in a vehiclecorrespondingly to undulation of a road surface; detecting an angularvelocity about a horizontal axis orthogonal to a travel direction of thevehicle generated in the vehicle correspondingly to the undulation ofthe road surface; and calculating a velocity in the travel direction ofthe vehicle on the basis of the acceleration in the vertical directionand the angular velocity about the horizontal axis.

According to another embodiment of the present invention, there isprovided a navigation device including: a vertical directionacceleration detection portion that detects an acceleration in avertical direction generated in a vehicle correspondingly to undulationof a road surface; a horizontal direction angular velocity detectionportion that detects an angular velocity about a horizontal axisorthogonal to a travel direction of the vehicle generated in the vehiclecorrespondingly to the undulation of the road surface; a velocitycalculation portion that calculates a velocity in the travel directionof the vehicle on the basis of the acceleration in the verticaldirection and the angular velocity about the horizontal axis; a verticaldirection angular velocity detection portion that calculates an angularvelocity about a vertical axis that is perpendicular to the traveldirection; an angle calculation portion that calculates an angle bywhich the vehicle has turned on the basis of the angular velocity aboutthe vertical axis; and a position calculation portion that calculates aposition of the vehicle on the basis of the velocity in the traveldirection calculated by the velocity calculation portion and the anglecalculated by the angle calculation portion.

According to the embodiments of the present invention, it becomespossible to detect the acceleration in the vertical direction and theangular velocity about the horizontal axis orthogonal to the traveldirection both generated correspondingly to undulation of the roadsurface and to calculate the velocity in the travel direction of thevehicle on the basis of the acceleration in the vertical direction andthe angular velocity about the horizontal axis in all the roadenvironments.

According to the embodiments of the present invention, by detecting theacceleration in the vertical direction and the angular velocity aboutthe horizontal axis orthogonal to the travel direction both generatedcorrespondingly to undulation of the road surface and by calculating thevelocity in the travel direction of the vehicle on the basis of theacceleration in the vertical direction and the angular velocity aboutthe horizontal axis, it becomes possible to provide a velocitycalculation device, a velocity calculation method, and a navigationdevice capable of calculating the velocity of the vehicle at highaccuracy in all the road environments under any circumstance.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1A and FIG. 1B are diagrams schematically showing states where avehicle is traveling on concave and convex road surfaces, respectively;

FIG. 2 is a diagram schematically showing a state where the vehicle istraveling along a curve;

FIG. 3 is a diagram schematically showing a current position calculationmethod using a velocity and an angle;

FIG. 4 is a diagram schematically showing the overall configuration of aPND;

FIG. 5 is a diagram schematically showing definitions of the coordinatesystem of the PND;

FIG. 6 is a diagram schematically showing a sensor configuration of thePND;

FIG. 7 is a diagram schematically showing a circuit diagram of the PND;

FIG. 8 is a diagram schematically showing the configuration of avelocity calculation portion;

FIG. 9 is a diagram schematically showing a relation of an altitude andan angle;

FIG. 10A and FIG. 10B are diagrams schematically showing states of aroad surface angle at a low velocity;

FIG. 11A and FIG. 11B are diagrams schematically showing states of theroad angle at a high velocity;

FIG. 12 is a diagram schematically showing a state of the road surfaceangle at an extremely low velocity;

FIG. 13 is a diagram schematically showing a state of an oscillation bya cradle;

FIG. 14 is a diagram schematically showing an additive acceleration andan additive angular velocity after high-pass filter processing;

FIG. 15A through FIG. 15H are diagrams schematically showing theadditive angular velocities Fourier transformed in every 4096 datapoints;

FIG. 16A through FIG. 16H are diagrams schematically showing theadditive angular velocities Fourier transformed in every 4096 datapoints;

FIG. 17A through FIG. 17D are diagrams schematically showing acomparison of the low-pass filter processing on the additiveacceleration;

FIG. 18A through FIG. 18D are diagrams schematically showing acomparison of the low-pass filter processing on the additive angularvelocity;

FIG. 19 is a diagram schematically showing a relation of a frontacceleration and a rear acceleration at a low velocity;

FIG. 20A and FIG. 20B are diagrams schematically showing a relation ofthe front acceleration and the rear acceleration at a medium velocityand a high velocity;

FIG. 21A through FIG. 21F are diagrams schematically showing examples ofsimulations of an acceleration, a pitch rate, and a velocity at threemount positions;

FIG. 22 is a diagram schematically showing a relation of a maximum valueand a minimum value;

FIG. 23 is a diagram schematically showing a relation of a velocity anda data point number;

FIG. 24A and FIG. 24B are diagrams schematically showing states of anacceleration and a pitch rate in different arc lengths;

FIG. 25 is a flowchart used to describe a current position calculationprocessing procedure using velocity calculation processing;

FIG. 26A and FIG. 26B are diagrams schematically showing examples ofmeasurement results of an acceleration, an angular velocity, and avelocity;

FIG. 27A and FIG. 27B are diagrams schematically showing a comparison(1) of the measurement result with the reference;

FIG. 28A and FIG. 28B are diagrams schematically showing a comparison(2) of the measurement result with the reference;

FIGS. 29A and 29B are diagrams schematically showing a comparison (3) ofthe measurement result with the reference;

FIGS. 30A and 30B are diagrams schematically showing a comparison (4) ofthe measurement result with the reference;

FIGS. 31A and 31B are diagrams schematically showing a comparison (5) ofthe measurement result with the reference;

FIG. 32A through FIG. 32C are diagrams schematically showing acomparison (1) of the measurement result with the reference at a curve;

FIG. 33A through FIG. 33C are diagrams schematically showing acomparison (2) of the measurement result with the reference at a curve;

FIG. 34A through FIG. 34C are diagrams schematically showing acomparison (3) of the measurement result with the reference at a curve;

FIG. 35A and FIG. 35B are diagrams schematically showing a comparison ofa path on a map with a travel track;

FIG. 36 is a diagram schematically showing a comparison of themeasurement result by the PND mounted on a compact vehicle and thevelocity and the distance based on the GPS signals;

FIG. 37 is a diagram schematically showing a comparison of themeasurement result by the PND mounted on a minivan vehicle and thevelocity and the distance based on the GPS signals; and

FIG. 38 is a diagram schematically showing an example of use in anotherembodiment of the present invention.

DESCRIPTION OF THE PREFERRED EMBODIMENTS

Hereinafter, embodiments of the present invention will be described indetail with reference to the drawings.

(1) Fundamental Principle

In embodiments of the present invention, a portable navigation device(hereinafter, referred to also as the PND (Personal Navigation Device))is used as a navigation device, and the fundamental principle tocalculate a velocity and a current position of the vehicle using the PNDwill be described.

(1-1) Velocity Calculation Principle

Practically, the vehicle seldom travels on a flat road while it istraveling on roads. The vehicle actually travels on a road in a concaveshape when viewed as a whole as is shown in FIG. 1A and a road in aconvex shape when viewed as a while as is shown in FIG. 1B.

In the coordinate system of the vehicle used herein, the X axisindicates the front-rear direction of the vehicle, the Y axis indicatesthe horizontal direction orthogonal to the X axis, and the Z axisindicates the top-bottom direction.

When the vehicle travels on a concave road (FIG. 1A), the PND mounted,for example, on the dashboard of the vehicle detects a downwardacceleration α_(z) along the Z axis using a triaxial acceleration sensorprovided to the PND at the sampling frequency, for example, of 50 [Hz].

The PND also detects an angular velocity (hereinafter, referred to alsoas the pitch rate) ω_(y) about the Y axis orthogonal to the traveldirection using a Y axis gyro sensor provided to the PND at the samplingfrequency of 50 [Hz].

Herein, for the PND, it is defined that the downward acceleration α_(z)along the Z axis is the positive and the pitch rate ω_(y) when a virtualcircle formed along the concave road surface as shown in FIG. 1Aundergoes an upward longitudinal rotation with respect to the traveldirection is the positive.

The PND is configured to calculate a velocity V in the travel direction50 times per second in accordance with Equation (1) below using theacceleration α_(z) detected by the triaxial acceleration sensor and thepitch rate ω_(y) detected by the Y axis gyro sensor.

$\begin{matrix}{V = \frac{\alpha_{z}}{\omega_{y}}} & (1)\end{matrix}$

When the vehicle travels on a convex road (FIG. 1B), the PND detects anupward acceleration α_(z)′ along the Z axis using the triaxialacceleration sensor provided to the PND at the sampling frequency, forexample, of 50 [Hz] and also detects a pitch rate ω_(y)′ about the Yaxis using the Y axis gyro sensor provided to the PND at the samplingfrequency, for example, of 50 [Hz].

The PND is configured to calculate a velocity V′ in the travel direction50 times per second in accordance with Equation (2) below using theacceleration α_(z)′ detected by the triaxial acceleration sensor and thepitch rate ω_(y)′ detected by the Y axis gyro sensor.

$\begin{matrix}{V^{\prime} = \frac{\alpha_{z}^{\prime}}{\omega_{y}^{\prime}}} & (2)\end{matrix}$

Herein, for ease of description, the negative acceleration α_(z) isdescribed as the acceleration α_(z)′. The triaxial acceleration sensoractually detects the acceleration α_(z)′ as a negative value of theacceleration α_(z). The same can be said with the pitch rate ω_(y)′. Inother words, although the negative pitch rate ω_(y) is described as thepitch rate ω_(y)′, the Y axis gyro sensor actually detects the pitchrate ω_(y)′ as a negative value of the pitch rate ω_(y). Accordingly,the velocity V′ is actually calculated as the velocity V.

(1-2) Current Position Calculation Principle

The current position calculation principle to calculate a currentposition on the basis of the velocity V calculated using the velocitycalculation principle described above and the angular velocity about theZ axis will now be described.

As is shown in FIG. 2, the PND detects an angular velocity (hereinafter,referred to also as the yaw rate) ω_(z) about the Z axis when thevehicle is turning to the left using a Z axis gyro sensor provided tothe PND at the sampling frequency, for example, of 50 [Hz].

The PND then finds, as is shown in FIG. 3, an amount of change from thelast position P0 to the current position P1 on the basis of the velocityV at the last position P0 and an angle θ obtained by multiplying the yawrate ω_(z) detected by the gyro sensor by a sampling cycle (herein, 0.02[s]). The PND is configured to calculate the current position P1 byadding the amount of change to the last position P0.

(2) Configuration of PND

A concrete configuration of a car navigation device that calculates avelocity and a current position of the vehicle using the fundamentalprinciple according an embodiment of the present invention will now bedescribed.

(2-1) Outward Appearance Configuration of PND

As is shown in FIG. 4, a PND 1 is provided with a display portion 2 onthe front face of the PND 1 and is configured to display a map image orthe like corresponding to map data stored, for example, in an internalnon-volatile memory (not shown) of the PND 1 on the display portion 2.

The PND 1 is held by a cradle 3 attached onto the dashboard of thevehicle via a suction disc 3A and the PND 1 and the cradle 3 aremechanically and electrically connected to each other.

The PND 1 therefore operates on source power supplied from the batteryof the vehicle via the cradle 3, and when removed from the cradle 3, itoperates in an independent state on power supplied from the internalbattery.

The PND 1 is provided in such a manner that the display portion 2 issubstantially perpendicular to the travel direction of the vehicle. Asis shown in FIG. 5, in the coordinate system of the PND 1 in thisinstance, the X axis indicates the front-rear direction (traveldirection) of the vehicle, the Y axis indicates the horizontal directionorthogonal to the X axis, and the Z axis indicates the top-bottomdirection.

In this coordinate system, the travel direction of the vehicle isdefined as the positive of the X axis, the right direction as thepositive of the Y axis, and the downward direction as the positive ofthe Z axis.

(2-2) Sensor Configuration of PND

As is shown in FIG. 6, the PND 1 includes a triaxial acceleration sensor4, a Y axis gyro sensor 5, a Z axis gyro sensor 6, and a pressure sensor7, all of which are provided inside.

The triaxial acceleration sensor 4 is configured to detect each of anacceleration α_(x) along the X axis, an acceleration α_(y) along the Yaxis, and an acceleration α_(z) along the Z axis as a voltage value.

The Y axis gyro sensor 5, the Z axis gyro sensor 6, and the pressuresensor 7 are configured to detect a pitch rate ω_(y) about the Y axis, ayaw rate ω_(z) about the Z axis, and an ambient air pressure PR,respectively, as voltage values.

(2-3) Circuit Configuration of PND

As is shown in FIG. 7, a control portion 11 of the PND 1 is formed of aCPU (Central Processing Unit), and is configured to perform overallintegrated control by a basic program read out from a memory portion 12formed, for example, of a non-volatile memory.

The PND 1 is also configured to perform velocity calculation processingdescribed below according to various application programs read out bythe control portion 11 from the memory portion 12.

The control portion 11 is configured to function as a GPS processingportion 21, a velocity calculation portion 22, an angle calculationportion 23, an altitude calculation portion 24, a position calculationportion 25, and a navigation portion 26 when performing the velocitycalculation processing and the like.

In the PND 1, GPS signals from a plurality of GPS satellites received ata GPS antenna ANT are sent to the GPS processing portion 21 of thecontrol portion 11.

The GPS processing portion 21 acquires current position data NPD1obtained by precisely positioning a current position of the vehicle onthe basis of track data obtained by demodulating each of a plurality ofGPS signals and distance data about distances from a plurality of GPSsatellites to the vehicle, and sends the acquired data to the navigationportion 26.

The navigation portion 26 is configured to read out map data of theperiphery including the current position of the vehicle on the basis ofthe current position data NPD1 from the memory portion 12 so as tocreate a map image including the current position, and to display themap image by outputting the map image to the display portion 2.

Incidentally, the triaxial acceleration sensor 4 detects theaccelerations α_(x), α_(y), and α_(z) at the sampling frequency, forexample, of 50 [Hz]. Of the accelerations α_(x), α_(y), and α_(z), itsends acceleration data AD indicating the acceleration α_(z) to theacceleration calculation portion 22 of the control portion 11.

The Y axis gyro sensor 5 detects the pitch rate ω_(y) at the samplingfrequency, for example, of 50 [Hz] and sends pitch rate data PDindicating the pitch rate ω_(y) to the velocity calculation portion 22of the control portion 11.

The velocity calculation portion 22 calculates the velocity V 50 timesper second using Equation (1) above on the basis of the accelerationα_(z) corresponding to the acceleration data AD supplied from thetriaxial acceleration sensor 4 and the pitch rate ω_(y) corresponding tothe pitch rate data PD supplied from the Y axis gyro sensor 5, and sendsvelocity data VD indicating the velocity V to the position calculationportion 25.

The Z axis gyro sensor 6 detects the yaw rate ω_(z) at the samplingfrequency, for example, of 50 [Hz] and sends yaw rate data YD indicatingthe yaw rate ω_(z) to the angle calculation portion 23 of the controlportion 11.

The angle calculation portion 23 calculates an angle θ when the vehicleis turning to the right or the left by multiplying the yaw rate Wcorresponding to the yaw rate data YD supplied from the Z axis gyrosensor 6 by a sampling cycle (herein, 0.02 [s]) and sends angle data DDindicating the angle θ to the position calculation portion 25.

The position calculation portion 25 finds an amount of change from thelast position P0 to the current position P1 as shown in FIG. 3 on thebasis of the velocity V corresponding to the velocity data VD suppliedfrom the velocity calculation portion 22 and the angle θ correspondingto the angle data DD supplied from the angle calculation portion 23. Theposition calculation portion 25 calculates the current position P1 byadding the amount of change to the last position P0 and sends currentposition data NPD2 indicating the current position P1 to the navigationportion 26.

Meanwhile, the pressure sensor 7 detects an ambient pressure PR at thesampling frequency, for example, of 50 [Hz] and sends pressure data PRDindicating the pressure PR to the altitude calculation portion 24.

The altitude calculation portion 24 calculates an altitude of thevehicle on the basis of the pressure PR corresponding to the pressuredata PRD supplied from the pressure sensor 7 and sends altitude data HDindicating the altitude to the navigation portion 26.

The navigation portion 26 is configured to read out map data of theperiphery including the current position of the vehicle from the memoryportion 12 on the basis of the current position data NPD2 supplied fromthe position calculation portion 25 and the altitude data HD suppliedfrom the altitude calculation portion 24 so as to create a map imageincluding the current position, and to display the map image byoutputting the map image to the display portion 2.

(3) Velocity Calculation Processing

The velocity calculation processing to calculate the velocity V by thevelocity calculation portion 22 on the basis of the acceleration α_(z)corresponding to the acceleration data AD supplied from the triaxialacceleration sensor 4 and the pitch rate ω_(y) corresponding to thepitch rate data PD supplied from the Y axis gyro sensor 5 will now bedescribed in detail.

When performing the velocity calculation processing, as is shown in FIG.8, the velocity calculation portion 22 functions as a data acquisitionportion 31, a high-pass filter portion 32, a low-pass filter portion 33,a velocity computation portion 34, a smoothing and noise removal portion35, and a velocity output portion 36.

The data acquisition portion 31 of the velocity calculation portion 22acquires the acceleration data AD supplied from the triaxialacceleration sensor 4 and the pitch rate data PD supplied from the Yaxis gyro sensor 5 and sends the acceleration data AD and the pitch ratedata PD to the high-pass filter portion 32.

The high-pass filter portion 32 cuts off direct current components ofthe acceleration data AD and the pitch rate data PD supplied from thedata acquisition portion 31 and sends the resulting acceleration dataAD1 and pitch rate data PD1 to the low-pass filter portion 33.

The low-pass filter portion 33 applies low-pass filter processingdescribed below to the acceleration data AD1 and the pitch rate data PD1supplied from the high-pass filter portion 32 and sends the resultingacceleration data AD2 and pitch rate data PD2 to the velocitycomputation portion 34.

The velocity computation portion 34 applies velocity computationprocessing described below to the acceleration data AD2 and the pitchrate data PD2 supplied from the low-pass filter portion 33 and sends theresulting velocity data VD1 to the smoothing and noise removal portion35.

The smoothing and noise removal portion 35 applies smoothing and noiseremoval processing described below to the velocity data V1 supplied fromthe velocity computation portion 34 and sends the resulting velocitydata VD to the velocity output portion 36.

The velocity output portion 36 outputs the velocity data VD suppliedfrom the smoothing and noise removal portion 35 to the positioncalculation portion 25.

As has been described, the velocity calculation portion 22 is configuredto calculate the velocity V of the vehicle on the basis of theacceleration data AD supplied from the triaxial acceleration sensor 4and the pitch rate data PD supplied from the Y axis gyro sensor 5.

(3-1) Low-Pass Filter Processing

The low-pass filter processing applied by the low-pass filter portion 33to the acceleration data AD1 and the pitch rate data PD1 supplied fromthe high-pass filter portion 32 will now be described in detail.

Incidentally, a relation of an altitude H based on the pressure PRcorresponding to the pressure data PND acquired by the pressure sensor 7and an angle φ about the Y axis with respect to the horizontal directionbased on the pitch rate ω_(y) corresponding to the pitch rate data PDacquired by the Y axis gyro sensor 5 is shown in FIG. 9. For the angle(referred to herein, it is defined that the upward direction withrespect to the travel direction (X axis) is the positive.

As is obvious from a fact in FIG. 9 that when the altitude H lowersabruptly from about data points 12001 (240 [s]), that is, when thevehicle is running down a downhill slope, the angle φ decreases abruptlyfrom about 0.5 [deg] to about −2.5 [deg], there is a correlation betweenthe altitude H and the angle T.

When the altitude H changes as above, the angle φ also changes inassociation with a change of the altitude H. It is therefore understoodthat the PND 1 is able to detect undulation of the road surface in thetravel direction of the vehicle using the Y axis gyro sensor 5.

The angle φ in FIG. 9 alone is shown in FIG. 10A. FIG. 10B shows theangle φ from data points 5001 to data points 6001 of FIG. 10A while thevehicle is traveling at a low velocity lower than 20 [km] per hour. Asis obvious also from FIG. 10B, the angle φ oscillates one or two timeper second.

Hence, the PND 1 mounted on the vehicle detects the angle φ based on thepitch rate ω_(y) corresponding to the pitch rate data PD acquired by theY axis gyro sensor 5 as an oscillation of 1 to 2 [Hz] while the vehicleis traveling at a low velocity lower than 20 [km] per hour.

Also, as with FIG. 10A, FIG. 11A shows the angle T of FIG. 9 alone. FIG.11B shows the angle φ from data points 22001 to data points 23001 ofFIG. 11A while the vehicle is traveling at a high velocity of 60 [km]per hour or higher.

According to these drawings, the PND 1 also detects the angle φ based onthe pitch rate ω_(y) corresponding to the pitch rate data PD acquired bythe Y axis gyro sensor 5 as an oscillation of 1 to 2 [Hz] while thevehicle is traveling at a high velocity of 60 [km] per hour or higher.

Further, as is shown in FIG. 12, the PND 1 also detects the angle Tbased on the pitch rate ω_(y) corresponding to the pitch rate data PDacquired by the Y axis gyro sensor 5 as an oscillation of 1 to 2 [Hz]while the vehicle is traveling at an extremely low velocity lower than10 [km] per hour.

Hence, when the PND 1 detects the pitch rate ω_(y) from the Y axis gyrosensor 5, it detects the pitch rate ω_(y) as an oscillation of 1 to 2[Hz] regardless of the travel velocity of the vehicle.

Incidentally, the PND 1 is held by the cradle 3 attached to thedashboard of the vehicle via the suction disc 3A. As is shown in FIG.13, the cradle 3 includes a main body portion 3B provided above thesuction disc 3A and a PND supporting portion 3D that is supported on asupporting point 3C provided to the main body portion 3B at apredetermined height position at one end and supports the PND 1 at theother end.

Hence, when the vehicle oscillates correspondingly to undulation of theroad surface, the PND 1 oscillates in the top-down direction about thesupporting point 3C of the PND supporting portion 3D, for example, atthe acceleration α_(c) and the angular velocity ω_(c).

The triaxial acceleration sensor 4 therefore actually detects anacceleration (hereinafter, referred to as the additive acceleration)α_(cz) obtained by adding an acceleration α_(c) associated with anoscillation about the supporting point 3C of the PND supporting portion3D to the acceleration α_(z) (FIG. 1) in the Z axis direction generatedwhen the vehicle oscillates correspondingly to undulation of the roadsurface.

Also, the Y axis gyro sensor 5 actually detects an angular velocity(hereinafter, referred to as the additive angular velocity) ω_(cy)obtained by adding an angular velocity ω_(c) associated with anoscillation about the supporting point 3C of the PND supporting portion3D to the pitch rate ω_(y) (FIG. 1) about the Y axis generated when thevehicle oscillates correspondingly to undulation of the road surface.

The low-pass filter portion 33 therefore actually acquires theacceleration data AD1 indicating the additive acceleration α_(cz) andthe pitch rate data PD1 indicating the additive angular velocity ω_(cy)via the data acquisition portion 31 and the high-pass filter portion 32.

The additive acceleration α_(cz) corresponding to the acceleration dataAD1 and the additive angular velocity ω_(cy) corresponding to the pitchrate data PD1 after the high-pass filter processing is applied by thehigh-pass filter portion 32 are shown in FIG. 14. FIG. 15A through 15Hshow graphs of the additive angular velocities ω_(cy) shown in FIG. 14that are Fourier transformed in every 4096 data points.

To be more concrete, FIG. 15A is a graph of the Fourier transformedadditive angular velocity ω_(cy) from data points 1 to 4096 of FIG. 14.Likewise, FIGS. 15B, 15C, and 15D are graphs of the Fourier transformedadditive angular velocities ω_(cy) from data points 4097 to 8192, fromdata points 8193 to 12288, and from data points 12289 to 16384 of FIG.14, respectively.

Also, FIGS. 15E, 15F, 15G, and 15H are graphs of the Fourier transformedadditive angular velocities ω_(cy) from data points 16385 to 20480, fromdata points 20481 to 24576, from data points 24577 to 28672, and fromdata points 28673 to 32768 of FIG. 14, respectively.

Of FIGS. 15A through 15H, as are shown noticeably in FIG. 15C through15H, a frequency component at 1 to 2 [Hz] and a frequency component atabout 15 [Hz] indicate large values.

In other words, the PND 1 detects the additive angular velocity ω_(cy),which is a synthesis of the pitch rate ω_(y) oscillating at 1 to 2 [Hz]by undulation of the road surface as described above and the angularvelocity ω_(c) oscillating at about 15 [Hz] by the cradle 3 holding thePND 1, using the Y axis gyro sensor 5.

Meanwhile, FIGS. 16A through 16H show graphs of the additiveaccelerations α_(cz) shown in FIG. 14 that are Fourier transformed inevery 4096 data points.

To be more concrete, FIG. 16A is a graph of the Fourier transformedadditive acceleration α_(cz) from data points 1 to 4096 of FIG. 14.Likewise, FIGS. 16B, 16C, and 16D are graphs of the Fourier transformedadditive accelerations α_(cz) from data points 4097 to 8192, from datapoints 8193 to 12288, and from the data points 12289 to 16384 of FIG.14, respectively.

Also, FIGS. 16E, 16F, 16G, and 16H are graphs of the Fourier transformedadditive accelerations α_(cz) from data points 16385 to 20480, from datapoints 20481 to 24576, from data points 24577 to 28672, and from datapoints 28673 to 32768 of FIG. 14, respectively.

Because a frequency component at 1 to 2 [Hz] and a frequency componentat about 15 [Hz] are generated in the additive angular velocities ω_(cy)(FIGS. 15C through 15H), it is anticipated that a frequency component at1 to 2 [Hz] and a frequency component at about 15 [Hz] are generatedalso in the additive accelerations α_(cz).

In other words, the PND 1 detects the additive acceleration α_(cz),which is a synthesis of the acceleration α_(z) oscillating at 1 to 2[Hz] by undulation of the road surface as described above and theacceleration α_(c) oscillating at about 15 [Hz] by the cradle 3 holdingthe PND 1, using the triaxial acceleration sensor 4.

The low-pass filter portion 33 is therefore configured to apply thelow-pass filter processing to the acceleration data AD1 and the pitchrate data PD1 supplied from the high-pass filter portion 32 so as toremove the frequency components at about 15 [Hz], that is, theacceleration α_(c) and the angular velocity ω_(c) generated because thePND 1 is held by the cradle 3.

The graph of FIG. 16H is converted to the graph shown in FIG. 17A byusing the logarithmic axis as the ordinate. An IIR (Infinite ImpulseResponse) filter at the cutoff frequency of 2 [Hz] is applied to theadditive acceleration α_(cz) from data points 28673 to 32768 two, four,and six times followed by Fourier transformation and the graphs thusobtained are shown in FIGS. 17B, 17C, and 17D, respectively.

Also, the graph of FIG. 15H is converted to the graph of FIG. 18A byusing the logarithmic axis as the ordinate. As with the additiveacceleration α_(cz), the IIR filter at the cutoff frequency of 2 [Hz] isapplied to the additive angular velocity ω_(cy) from data points 28673to 32768 two, four, and six times followed by Fourier transformation andthe graphs thus obtained are shown in FIGS. 18B, 18C, and 18D,respectively.

As are shown in FIGS. 17B through 17D and FIGS. 18B through 18D, the PND1 is able to remove frequency components at about 15 [Hz] generatedbecause the PND 1 is held by the cradle 3 by applying the IIR filter atthe cutoff frequency of [Hz] to the acceleration data AD1 and the pitchrate data PD1 supplied from the high-pass filter portion 32 four timesor more.

Accordingly, the low-pass filter portion 33 according to an embodimentof the present invention applies the IIR filter at the cutoff frequencyof 2 [Hz] to the acceleration data AD1 and the pitch rate data PD1supplied from the high-pass filter portion 32 four times and sends theresulting acceleration data AD2 and the pitch rate data PD2 to thevelocity computation portion 34.

The low-pass filter portion 33 is therefore able to extract only theacceleration α_(z) generated by undulation of the road surface byremoving the acceleration α_(c) associated with an oscillation in thecradle 3 about the supporting point 3C of the PND supporting portion 3Dfrom the additive acceleration α_(cz).

Also, the low-pass filter portion 33 is able to extract only the pitchrate ω_(y) generated by undulation of the road surface by removing theangular velocity ω_(c) associated with an oscillation in the cradle 3about the supporting point 3C of the PND supporting portion 3D from theadditive angular velocity ω_(cy).

(3-2) Velocity Computation Processing

The velocity computation processing to calculate the velocity V by thevelocity computation portion 34 on the basis of the acceleration dataAD2 and the pitch rate data PD2 supplied from the low-pass filterportion 33 will now be described in detail.

The accelerations α_(z) corresponding to the acceleration data AD2 onthe front side and the rear side when the vehicle travels, respectively,at a low velocity lower than 20 [km] per hour, a medium velocity lowerthan 60 [km] per hour, and a high velocity at 60 [km] per hour or higherwhile the PND 1 is mounted on the dashboard on the front side of thevehicle and in the vicinity of the rear window on the rear side of thevehicle are shown in FIG. 19 and FIGS. 20A and 20B.

In FIG. 19, and FIGS. 20A and 20B, the acceleration α_(z) detected bythe PND 1 mounted on the front side is referred to as the frontacceleration and the acceleration α_(z) detected by the PND 1 mounted onthe rear side is referred to as the rear acceleration.

As is obvious from FIG. 19 and FIGS. 20A and 20B, it is understood thatthe phase of the rear acceleration lags from the front accelerationregardless of the travel velocity of the vehicle. The phase lag issubstantially equal to a value obtained by dividing a wheel base, whichis a distance between the front wheel shaft and the rear wheel shaft ofthe vehicle, by the travel velocity.

FIGS. 21A through 21C show examples of the simulation results indicatinga relation of the acceleration α_(z) corresponding to the accelerationdata AD2 and the pitch rate ω_(y) corresponding to the pitch rate dataPD2 when the PND 1 is mounted on the dashboard (corresponding to 30% ofthe wheel base from the front wheel shaft), at the center, and on therear wheel shaft of the vehicle, respectively. FIGS. 21D through 21Fshow the results when the velocity V is calculated in accordance withEquation (1) above on the basis of the acceleration α_(z) and thepitching rate ω_(y) obtained from the simulation results shown in FIGS.21A through 21C, respectively.

The simulation was performed with the assumption that a vehicle havingthe wheel base of 2.5 [m] travels at a velocity of 5 [m/s] on the roadsurface undulating in sine waves having an amplitude of 0.1 [m] and awavelength of 20 [m].

As is obvious from FIGS. 21A through 21C, the phase of the accelerationα_(z) lags as the PND 1 is mounted on the vehicle at the position closerto the rear side. Meanwhile, there is no phase lag in the pitch rateω_(y) regardless of the mount position of the PND 1 in the vehicle.

Hence, as is shown in FIG. 21B, in a case where the PND 1 is mounted atthe center of the vehicle, there is substantially no phase lag betweenthe acceleration α_(z) and the pitch rate ω_(y). Hence, as is shown inFIG. 21E, the velocity V calculated in accordance with Equation (1)above is substantially constant.

However, as are shown in FIGS. 21A and 21C, when the mount position ofthe PND 1 shifts forward or rearward with respect to the center of thevehicle, there is a considerable phase lag between the acceleration 11,and the pitch rate ω_(y). Accordingly, as are shown in FIGS. 21D and21F, the velocity V calculated in accordance with Equation (1) above hasa significant error in comparison with the velocity V in a case wherethe PND 1 is mounted at the center of the vehicle (FIG. 21E) because ofthe phase lag between the acceleration α_(z) and the pitch rate W.

In particular, because the phase lag between the acceleration α_(z) andthe pitch rate ω_(y) becomes large when the velocity V of the vehicle isa low velocity lower than 20 [km] per hour, a calculation error of thevelocity V becomes large.

Accordingly, as is shown in FIG. 22, the velocity computation portion 34extracts a maximum value and a minimum value of the acceleration α_(z)corresponding to the acceleration data AD2 supplied from the low-passfilter portion 33 from a range of 25 data points or 75 data points aboutthe data point Pm corresponding to the last position P0 (FIG. 3) as amaximum acceleration α_(z,max) and a minimum acceleration α_(z,min),respectively.

Also, the velocity computation portion 34 extracts a maximum value and aminimum value of the pitch rate ω_(y) corresponding to the pitch ratedata PD2 supplied from the low-pass filter portion 33 from a range of 25data points or 75 data points about the data point Pm as a maximum pitchrate ω_(y,max) and a minimum pitch rate ω_(y,min), respectively.

The velocity computation portion 34 then calculates the velocity V inthe travel direction at the last position P0 (FIG. 3) in according withEquation (3) below, which is a modification of Equation (1) above, usingthe maximum acceleration α_(z,max) and the minimum accelerationα_(z,min) extracted from the acceleration data AD2 and the maximum pitchrate ω_(y,max) and the minimum pitch rate ω_(y,min) extracted from thepitch rate data PD2, and sends the resulting velocity data VD1 to thesmoothing and noise removal portion 35:

$\begin{matrix}{V = \frac{\alpha_{z,\max} - \alpha_{z,\min}}{\omega_{y,\max} - \omega_{y,\min}}} & (3)\end{matrix}$

Accordingly, by calculating the velocity V in accordance with Equation(3) above, even when there is a phase lag between the acceleration α_(z)corresponding to the acceleration data AD2 and the pitch rate ω_(y)corresponding to the pitch rate data PD2, the velocity computationportion 34 extracts the maximum acceleration α_(z,max) and the minimumacceleration α_(z,min), and the maximum pitch rate ω_(y,max) and theminimum pitch rate ω_(y,min) from the range wider than the phase lag,and is thereby able to remove the influence of the phase lag.

Incidentally, as is shown in FIG. 23, when the velocity computationportion 34 calculates the velocity V in the travel direction at the lastposition P0, it uses a range of 25 data points in a case where thevelocity (hereinafter, referred to as the previous value velocity)V_(n-1) at the second last position (not shown) is 0 [km] per hour to 35[km] per hour, and a range of 75 data points in a case where theprevious value velocity V_(n-1) exceeds 35 [km] per hour.

Also, when the velocity computation portion 34 calculates the velocity Vin the travel direction at the last position P0, it uses a range of 75data points in a case where the previous value velocity V_(n-1) is 35[km] per hour to 25 [km] per hour and a range of 25 data points in acase where the previous value velocity V_(n-1) is lower than 25 [km] perhour.

Hence, the velocity computation portion 34 switches the data ranges of25 data points and 75 data points in response to the velocity V whenextracting the maximum acceleration α_(z,max) and the minimumacceleration α_(z,min) and the maximum pitch rate ω_(y,max) and theminimum pitch rate ω_(y,min).

In this instance, in a case where the velocity V of the vehicle is at alow velocity, for example, 25 [km] per hour or lower, the accelerationα_(z) and the pitch rate ω_(y) vary abruptly with a slight change of theroad surface. The velocity computation portion 34 accordingly sets thedata range narrower in order to address such an abrupt variance.

By contrast, in a case where the velocity V of the vehicle is 35 [km]per hour or higher, because the influence of the suspension of thevehicle is large and the acceleration α_(z) and the pitch rate ω_(y)vary slowly, the velocity computation portion 34 sets the data rangewider in order to address such a slow variance.

In this manner, by switching the data ranges in response to the velocityV of the vehicle when extracting the maximum acceleration α_(z,max) andthe minimum acceleration α_(z,min) and the maximum pitch rate ω_(y,max)and the minimum pitch rate ω_(y,min), the velocity computation portion34 becomes able to reflect the conditions of the road surface and thevehicle corresponding to the velocity V. The calculation accuracy of thevelocity V can be therefore enhanced.

Also, when extracting the maximum acceleration α_(z,max) and the minimumacceleration α_(z,min) and the maximum pitch rate ω_(y,max) and theminimum pitch rate ω_(y,min), the velocity computation portion 34 isconfigured to provide the hysteresis characteristic such that changesthe data range between acceleration and deceleration.

Owing to this configuration, there is no need to frequently switch thedata ranges in the vicinity of the switching velocity of the data rangenecessary in a case where there is no hysteresis characteristic to thedata range when the velocity V is calculated. The velocity computationportion 34 is thus able to eliminate a calculation error of the velocityV caused by frequent switching. The calculation accuracy of the velocityV can be therefore enhanced further.

(3-3) Smoothing and Noise Removal Processing

The smoothing and noise removal processing applied by the smoothing andnoise removal portion 35 to the velocity data VD1 calculated by thevelocity computation portion 34 will now be described in detail.

The smoothing and noise removal portion 35 is configured to first applythe low-pass filter processing using a primary IIR in which the cutofffrequency is variable to the velocity data VD1 supplied from thevelocity computation portion 34.

To be more concrete, the smoothing and noise removal portion 35determines the cutoff frequency on the basis of the previous valuevelocity V_(n-1) when the velocity V in the travel direction at the lastposition P0 is calculated.

Herein, in the PND 1, when the travel velocity of the vehicle is a highvelocity, for example, at 60 [km] per hour or higher, the velocity Vcalculated by the velocity computation portion 34 contains considerablenoises and the velocity V varies noticeably. To avoid such aninconvenience, the smoothing and noise removal portion 35 uses alow-pass filter set with a low cutoff frequency when the previous valuevelocity V_(n-1) is 60 [km] per hour or higher.

On the contrary, when the previous value velocity V_(n-1) is lower than60 [km] per hour, the smoothing and noise removal portion 35 uses alow-pass filter set with a high cutoff frequency.

Incidentally, in a case where the velocity V calculated by the velocitycomputation portion 34 is an extremely low velocity lower than, forexample, 10 [km] per hour, the pitch rate ω_(y), which is the value of adenominator in Equation (1) or Equation (3) above, becomes smaller.Consequently, the velocity V calculated in accordance with Equation (1)or Equation (3) above may possibly become extremely larger than anactual value.

To avoid such an inconvenience, the smoothing and noise removal portion35 acquires the acceleration data AD2 and the pitch rate data PD2 towhich the low-pass filter processing has been applied from the low-passfilter portion 33, and in a case where the pitch rate ω_(y)corresponding to the pitch rate data PD2 is smaller than a predeterminedthreshold value, it determines that the velocity V is exceedingly highand sets the velocity V after the low-pass filter processing to 0.

Meanwhile, as is shown in FIG. 24A, in a case where an arc B1 ofundulation of the road surface is larger than the wheel base W of thevehicle, the PND 1 is able to calculate the velocity V precisely usingthe fundamental principle described above.

However, as is shown in FIG. 24B, for example, in a case where an arc B2of undulation of the road surface is smaller than the wheel base W, whenthe front wheels of the vehicle climb over the undulation, anacceleration α_(b) in the vertical direction with respect to the vehicleand an angular velocity ω_(b) about the Y axis centered on the rearwheels of the vehicle are generated.

In this instance, the PND 1 detects the acceleration α_(b) and theangular velocity ω_(b) (FIG. 24B) using the triaxial acceleration sensor4 and the Y axis gyro sensor 5, respectively, without detecting theacceleration 11, and the pitch rate ω_(y) (FIG. 24A) generated by anoscillation at 1 to 2 [Hz] corresponding to undulation of the roadsurface.

The acceleration α_(b) takes a larger value than the acceleration α_(z)generated when the arc B1 of undulation of the road surface is largerthan the wheel base W. Also, the angular velocity ω_(b) takes a largervalue than the pitch rate ω_(y) generated when the arc B1 of undulationof the road surface is larger than the wheel base W of the vehicle.

Further, a velocity (hereinafter, referred to as the small arc velocity)V_(b) calculated in accordance with Equation (1) or Equation (3) aboveon the basis of the acceleration α_(b) and the angular velocity ω_(b)generated when the arc B2 of undulation of the road surface is smallerthan the wheel base W takes an extremely larger value than the velocityV calculated in accordance with Equation (1) or Equation (3) on thebasis of the acceleration α_(z) and the pitch rate ω_(y) generated whenthe arc B1 of undulation of the road surface is larger than the wheelbase W of the vehicle because the acceleration α_(b) varies larger thanthe angular velocity ω_(b).

Accordingly, in a case where the arc B2 of undulation of the roadsurface is smaller than the wheel base W of the vehicle, the velocitycalculation portion 22 in the PND 1 consequently calculates the velocityV as an excessively large value by calculating the small arc velocityV_(b) using the acceleration α_(b) and the angular velocity w.

In order to avoid such an inconvenience, the smoothing and noise removalportion 35 acquires the acceleration data AD2 and the pitch rate dataPD2 to which the low-pass filter processing has been applied from thelow-pass filter portion 33 and determines whether the acceleration α_(z)corresponding to the acceleration data AD2 and the pitch rate ω_(y)corresponding to the pitch rate data PD2 are larger than correspondingpredetermined threshold values.

In a case where the acceleration α_(z) corresponding to the accelerationdata AD2 and the pitch rate ω_(y) corresponding to the pitch rate dataPD2 are larger than the corresponding predetermined threshold values,the smoothing and noise removal portion 35 determines that the velocityV is excessively high, and does not use the velocity V to which thelow-pass filter processing has been applied but uses the previous valuevelocity V_(n-1). In other words, the smoothing and noise removalportion 35 is configured to use the previous value speed V_(n-1) whenthe velocity V takes an excessively large value at velocities other thanan extremely low velocity because it is highly likely that the velocityV is wrong.

As has been described, the smoothing and noise removal portion 35 isable to calculate the velocity V more precisely by setting the velocityV to 0 at an extremely low velocity in a case where the velocity V towhich the low-pass filter processing has been applied takes anexcessively large value and by using the previous value velocity V_(n-1)as the velocity V otherwise.

(4) Position Calculation Processing Procedure Using Velocity CalculationProcessing

The position calculation processing procedure by the control portion 11in the PND 1 to calculate a current position using the velocitycalculation processing described above will now be described using theflowchart of FIG. 25.

In practice, the control portion 11 begins the procedure in the startstep of Routine RT1 and proceeds to Step SP1 where it acquires theacceleration data AD detected by the triaxial acceleration sensor 4 andthe pitch rate data PD detected by the Y axis gyro sensor 5 using thedata acquisition portion 31 of the velocity calculation portion 22,after which it proceeds to following Step SP2.

In Step SP2, the control portion 11 applies the high-pass filterprocessing to the acceleration data AD and the pitch rate data PD usingthe high-pass filter portion 32 of the velocity calculation portion 22,and proceeds to following Step SP3.

In Step SP3, the control portion 11 applies the low-pass filterprocessing using a biquadratic IIR filter at the cutoff frequency, forexample, of 1 [Hz] to the acceleration data AD1 and the pitch rate dataPD1 to which the high-pass filter processing has been applied, using thelow-pass filter portion 33 of the velocity calculation portion 22, andproceeds to following Step SP4.

In Step SP4, the control portion 11 calculates the velocity V inaccordance with Equation (3) above on the basis of the accelerationα_(z) corresponding to the acceleration data AD2 and the pitch rateω_(y) corresponding to the pitch rate data PD2 to which the low-passfilter processing has been applied, using the velocity computationportion 34 of the velocity calculation portion 22, and proceeds tofollowing Step SP5.

In Step SP5, the control portion 11 applies the smoothing and noiseremoval processing to the velocity data VD indicating the velocity Vcalculated in Step SP4.

To be more concrete, the control portion 11 applies the low-pass filterprocessing at a variable cutoff frequency to the velocity data VD1indicating the velocity V calculated in Step SP4.

In a case where the control portion 11 determines that the velocity V towhich the low-pass filter processing has been applied is an excessivelylarge value, it sets the velocity V to 0 at an extremely low velocity,for example, lower than 10 [km] per hour and uses the previous valuevelocity V_(n-1) as the velocity V otherwise, and proceeds to followingStep SP6.

In Step SP6, the control portion 11 acquires the yaw data YD detected bythe Z axis gyro sensor 6 using the angle calculation portion 23, andproceeds to following Step SP7.

In Step SP7, the control portion 11 calculates angle data DD indicatingthe angle θ by multiplying the yaw rate ω_(z) corresponding to the yawrate data YD by 0.02 [s], which is a sampling cycle, using the anglecalculation portion 23, and proceeds to following Step SP8.

In Step SP8, the control portion 11 calculates the current position dataNPD2 on the basis of the velocity data VD to which the smoothing andnoise removal processing has been applied in Step SP5 and the angle dataDD calculated in Step SP8, and proceeds to following Step SP9.

In Step SP9, the control portion 11 reads out from the memory portion 12the map data of the periphery including the current position of thevehicle on the basis of the current position data NPD2 supplied from theposition calculation portion 25 so as to create a map image includingthe current position and outputs the map image to the display portion 2,after which it proceeds to following Step SP10 to end the processing.

(5) Measurement Results

Measurement results calculated by the velocity calculation processingdescribed above are shown in FIG. 26A through FIG. 37. FIG. 26A throughFIG. 35B show the measurement results by the PND 1 mounted on a sedanvehicle. FIG. 36 and FIG. 37 show the measurement results by the PND 1mounted on a compact vehicle and a minivan vehicle, respectively.

FIG. 26A shows the acceleration α_(z) and the pitch rate ω_(y)respectively corresponding to the acceleration data AD and the pitchrate date PD detected by the triaxial acceleration sensor 4 and the Yaxis gyro sensor 5, respectively. FIG. 26B shows the velocity Vcalculated in accordance with Equation (3) above using the accelerationα_(z) and the pitch rate ω_(y).

As is obvious from FIG. 26A and FIG. 26B, in the PND 1, the accelerationα_(z) increases with an increase of the velocity V of the vehiclewhereas the pitch rate ω_(y) takes a substantially constant value.

FIG. 27A through FIG. 31B show graphs of the velocity V calculated byperforming the velocity calculation processing and a distance Dcalculated using the velocity V by the PND 1 and graphs of a velocityV_(ref) calculated from a vehicle velocity pulse of the vehicle on whichthe PND 1 is mounted and a distance D_(ref) calculated using thevelocity V_(ref) for comparison with the velocity V and the distance D.FIG. 27A through FIG. 31B show graphs when the vehicle on which ismounted the PND 1 travels on different roads.

Herein, the velocity calculated from the vehicle velocity pulse of thevehicle is referred to also as the reference velocity and the distancecalculated using the reference velocity is referred to also as thereference distance.

FIG. 27A shows the velocity V calculated using the velocity calculationprocessing according to an embodiment of the present invention and thedistance D calculated using the velocity V. FIG. 27B shows the referencevelocity V_(ref) and the reference distance D_(ref) for comparison withthe velocity V and the distance D shown in FIG. 27A.

As are shown in FIG. 27A and FIG. 27B, the velocity V has asubstantially similarity relation with the reference velocity V_(ref)and the distance D calculated on the basis of the velocity V generatesonly a slight error of less than 10% with respect to the referencedistance D_(ref).

FIG. 28A shows the velocity V calculated using the velocity calculationprocessing according to an embodiment of the present invention and thedistance D calculated using the velocity V. FIG. 28B shows the referencevelocity V_(ref) and the reference distance D_(ref) for comparison withthe velocity V and the distance D shown in FIG. 28A.

Further, FIG. 29A shows the velocity V calculated using the velocitycalculation processing according to an embodiment of the presentinvention and the distance D calculated using the velocity V. FIG. 29Bshows the reference velocity V_(ref) and the reference distance D_(ref)for comparison with the velocity V and the distance D shown in FIG. 29A.

Further, FIG. 30A shows the velocity V calculated using the velocitycalculation processing according to an embodiment of the presentinvention and the distance D calculated using the velocity V. FIG. 30Bshows the reference velocity V_(ref) and the reference distance D_(ref)for comparison with the velocity V and the distance D shown in FIG. 30A.

Further, FIG. 31A shows the velocity V calculated using the velocitycalculation processing according to an embodiment of the presentinvention and the distance D calculated using the velocity V. FIG. 31Bshows the reference velocity V_(ref) and the reference distance D_(ref)for comparison with the velocity V and the distance D shown in FIG. 31A.

As with the velocity V shown in FIG. 26A, the velocities V shown in FIG.27A, FIG. 28A, FIG. 29A, FIG. 30A, and FIG. 31A have a substantiallysimilarity relation with the reference velocities V_(ref) shown in FIG.27B, FIG. 28B, FIG. 29B, FIG. 30B, and FIG. 31B, respectively, and thedistances D calculated on the basis of the velocities V generate only aslight error of less than 10% with respect to the reference distancesD_(ref).

FIG. 32A shows the graph of the velocity V calculated by the PND 1 usingthe velocity calculation processing and the distance D and FIG. 32Bshows the graph of the reference velocity V_(ref) and the referencedistance D_(ref) calculated from the reference V_(ref). Further, FIG.32C shows the graph of the yaw rate ω_(z) detected by the Z axis gyrosensor 6 in the PND 1.

The yaw rate ω_(z) shown in FIG. 32C indicates that the vehicle takes aright turn when the value thereof exceeds about 20 [deg/s] and thevehicle takes a left turn when the value thereof drops below about −20[deg/s].

Hence, as is shown in FIG. 32C, even in a case where the vehiclerepetitively takes a right turn and a left turn several times insuccession, the velocity V (FIG. 32A) calculated by the PND 1 has asubstantially similarity relation with the reference velocity V_(ref)(FIG. 32B) and the distance D calculated on the basis of the velocity Vgenerates only a slight error of less than 10% with respect to thereference distance D_(ref).

FIG. 33A shows the graph of the velocity V calculated by the PND 1 usingthe velocity calculation processing and the distance D when the vehicletravels a road different from the road in the case of FIG. 32A. FIG. 33B shows the graph of the reference velocity V_(ref) and the referencedistance D_(ref) calculated from the reference velocity V_(ref).Further, FIG. 33C shows the graph of the yaw rate ω_(z) detected by theZ axis gyro sensor 6.

Further, FIG. 34A shows the graph of the velocity V calculated by thePND 1 using the velocity calculation processing and the distance D in acase where the vehicle travels on a road different from the roads in thecases of FIGS. 32A and 33A. FIG. 34B shows the graph of the referencevelocity V_(ref) and the reference distance D_(ref) calculated from thereference velocity V_(ref). Further, FIG. 34C shows the graph of the yawrate ω_(z) detected by the Z axis gyro sensor 6.

It is also understood from these results that even when the vehicletravels along many curves, the velocity V calculated by the PND 1 has asubstantially similarity relation with the reference velocity V_(ref)and the distance D calculated on the basis of the velocity V generatesonly a slight error of less than 10% with respect to the referencedistance D_(ref).

FIG. 35B shows a travel track T plotting the current position calculatedby the PND 1 mounted on the vehicle when the vehicle travels from thestart S to the goal G along the path K on the map shown in FIG. 35A.

The travel track T (FIG. 35B) has substantially the same size as and asimilarity relation with the path K (FIG. 35A) the vehicle has traveled.It is therefore understood that the PND 1 is able to calculate thecurrent position substantially precisely.

FIG. 36 shows the velocity V and the distance D calculated by the PND 1mounted on a compact vehicle superimposed on a velocity V_(g) calculatedon the basis of GPS signals received via the GPS antenna ANT and adistance D_(g) calculated from the velocity V_(g) for comparison withthe velocity V and the distance D.

Hereinafter, the velocity calculated on the basis of the GPS signalsreceived via the GPS antenna ANT is referred to also as the GPS velocityand the distance calculated from the GPS velocity is referred to also asthe GPS distance.

FIG. 37 shows the velocity V and the distance D calculated by the PND 1mounted on a minivan vehicle superimposed on the GPS velocity V_(g)calculated on the basis of the GPS signals and the GPS distance D_(g)calculated from the GPS velocity V_(g) for comparison with the velocityV and the distance D.

As are shown in FIG. 36 and FIG. 37, the velocity V calculated by thePND 1 according to an embodiment of the present invention in a pluralityof vehicles each having a different vehicle size, that is, a differentwheel base, has a substantially similarity relation with the GPSvelocity V_(g) and the distance D calculated on the basis of thevelocity V generates only a slight error of less than 10% with respectto the GPS distance D_(g).

Incidentally, in FIG. 36 and FIG. 37, in a case where the PND 1 fails toreceive the GPS signals, for example, in a case where the vehicle goesinto a tunnel, the GPS velocity V_(g) is calculated as being 0.

(6) Operation and Advantage

With the configuration described above, the PND 1 detects theacceleration α_(z) in the Z axis direction perpendicular to the traveldirection of the vehicle generated by undulation of the road surfaceusing the triaxial acceleration sensor 4 and detects the pitch rateω_(y) about the Y axis orthogonal to the travel direction generated byundulation of the road surface using the Y axis gyro sensor 5.

The PND 1 is configured to calculate the velocity V in accordance withEquation (1) or Equation (3) above on the basis of the accelerationα_(z) detected by the triaxial velocity sensor 4 and the pitch rateω_(y) detected by the Y axis gyro sensor 5.

Hence, even when the PND 1 fails to receive GPS signals, it is able tocalculate the velocity V of the vehicle precisely in all the roadenvironments by the simple configuration using the triaxial accelerationsensor 4 and the Y axis gyro sensor 5 alone.

In addition, with the PND 1 of the configuration attachable to anddetachable from the vehicle, it is not necessary for the user to performa tedious operation to connect a cable used to transfer a vehiclevelocity pulse signal from the vehicle. The PND 1 therefore becomes moreconvenient.

Also, the PND 1 is configured to detect the yaw rate ω_(z) about the Zaxis perpendicular to the travel direction of the vehicle using the Zaxis gyro sensor 6 and to calculate the current position on the basis ofthe velocity V and the yaw rate ω_(z).

Accordingly, even when the PND 1 fails to receive GPS signals, it isable to calculate the current position of the vehicle precisely in allthe road environments by the simple configuration to provide thetriaxial acceleration sensor 4, the Y axis gyro sensor 5, and the Z axisgyro sensor 6 alone.

Further, the PND 1 is configured to apply the low-pass filter processingto the acceleration data AD1 and the pitch rate data PD1 whencalculating the velocity V. Hence, the PND 1 is able to remove thecomponents of the acceleration α_(c) and the angular velocity ω_(c)oscillating, for example, at about 15 [Hz] generated by the cradle 3 andmade of a frequency sufficiently large for the acceleration α_(z) andthe pitch rate ω_(y) oscillating at 1 to 2 [Hz] generated by undulationof the road surface.

Consequently, the PND 1 is able to calculate the velocity V furtherprecisely using the acceleration α_(z) and the pitch rate ω_(y) fromwhich the oscillation components generated by the cradle 3 have beenremoved.

Also, the PND 1 extracts the maximum acceleration α_(z,max) and theminimum acceleration α_(z,min) from a range of 25 data points or 75 datapoints about the data point Pm of the acceleration α_(z), and extractsthe maximum pitch rate ω_(y,max) and the minimum pitch rate ω_(y,min)from a range of 25 data points or 75 data points about the data point Pmof the pitch rate W.

The PND 1 then calculates the velocity V in accordance with Equation (3)above using the maximum acceleration α_(z,max) and the minimumacceleration α_(z,min) and the maximum pitch rate ω_(y,max) and theminimum pitch rate ω_(y,min).

Consequently, by using data points in a range wider than the phase lagbetween the acceleration and the pitch rate ω_(y) that varies with themount position of the PND 1 inside the vehicle, the PND 1 becomes ableto remove the influence of a phase lag between the acceleration α_(z)and the pitch rate ω_(y) described above.

Also, in a case where the velocity V calculated in accordance withEquation (3) above on the basis of the acceleration α_(z) and the pitchrate ω_(y) is an excessively large value, the PND 1 is able to calculatethe velocity V more precisely by setting the velocity V to 0 at anextremely low velocity and using the previous value velocity V_(n-1) asthe velocity V otherwise.

According to the configuration described above, by detecting theacceleration α_(z) in the Z axis direction generated by undulation ofthe road surface and the pitch rate ω_(y) about the Y axis generated byundulation of the road surface and by calculating the velocity V usingthe acceleration α_(z) and the pitch rate ω_(y), it becomes possible tocalculate the velocity V precisely in all the road environments.

(7) Other Embodiments

In the embodiment of the present invention described above, when thevelocity V is calculated, the velocity V is calculated in accordancewith Equation (3) above on the basis of the maximum accelerationα_(z,max) and the minimum acceleration α_(z,min) extracted from theacceleration α_(z) corresponding to the acceleration data AD2 and themaximum pitch rate ω_(y,max) and the minimum pitch rate ω_(y, min)extracted from the pitch rate ω_(y) corresponding to the angularvelocity DD2.

It should be appreciated, however, that the present invention is notlimited to the embodiment described above. The velocity computationportion 34 may be configured in such a manner that it finds, forexample, variances of 25 data points or 75 data points about the datapoint Pm corresponding to the last position P0 of the acceleration α_(z)corresponding to the acceleration data AD2 and the pitch rate ω_(y)corresponding to the pitch rate data PD2 supplied from the low-passfilter portion 33, so that the velocity computation portion 34calculates the velocity V by dividing the variance of the accelerationα_(z) by the variance of the pitch rate ω_(y).

Alternatively, the velocity computation portion 34 may find, forexample, deviations in a range of 25 data points or 75 data points aboutthe data point Pm corresponding to the last position P0 of theacceleration α_(z) corresponding to the acceleration data AD2 and thepitch rate ω_(y) corresponding to the pitch rate data PD2 supplied fromthe low-pass filter portion 33, so that the velocity computation portion34 calculates the velocity V by dividing the deviation of theacceleration α_(z) by the deviation of the pitch rate ω_(y).

Also, the embodiment of the present invention above has described a casewhere the accelerations α_(x), α_(y), α_(z) and the pitch rate ω_(y) andthe yaw rate W are measured by the triaxial acceleration sensor 4, the Yaxis gyro sensor 5, and the Z axis gyro sensor 6, respectively, at thesampling frequency of [Hz]. It should be appreciated, however, that thepresent invention is not limited to the embodiment described above. Thetriaxial acceleration sensor 4, the Y axis gyro sensor 5, and the Z axisgyro sensor 6 may be configured in such a manner so as to detect theaccelerations α_(x), α_(y), α_(z), the angular velocity ω_(y), and theangular velocity α_(z), respectively, at a predetermined samplingfrequency of other than 50 [Hz], for example, 10 [Hz].

Further, the embodiment of the present invention above has described acase where the velocity V is calculated using the acceleration α_(z) andthe pitch rate ω_(y) detected at the sampling frequency of 50 [Hz]. Itshould be appreciated, however, that the present invention is notlimited to the embodiment described above. The velocity calculationportion 22 in the PND 1 may be configured in such a manner that it findsaverage values of the acceleration α_(z) and the pitch rate W detectedat the sampling frequency of 50 [Hz] in every 25 data points andcalculates the velocity V using the average values of the accelerationα_(z) and the pitch rate ω_(y).

In this case, by finding the average values of the acceleration α_(z)and the pitch rate ω_(y) detected at the sampling frequency of 50 [Hz],for example, in every 25 data points, the velocity calculation portion22 in the PND 1 consequently calculates the velocity V only two timesper second. The control portion 11 in the PND 1 therefore reduces theprocessing load for the velocity calculation processing.

Further, the embodiment of the present invention above has described acase where the high-pass filter processing is applied by the high-passfilter portion 32 to the acceleration data AD and the pitch rate data PDdetected by the triaxial acceleration sensor 4 and the Y axis gyrosensor 5, respectively. It should be appreciated, however, that thepresent invention is not limited to the embodiment described above. ThePND 1 may be configured in such a manner that the high-pass filterprocessing is not applied to the acceleration data AD and the pitch ratedata PD detected by the triaxial acceleration sensor 4 and the Y axisgyro sensor 5, respectively.

Further, the embodiment of the present invention above has described acase where the high-pass filter processing and the low-pass filterprocessing are applied by the high-pass filter portion 32 and thelow-pass filter portion 33, respectively, to the acceleration data ADand the pitch rate data PD detected by the triaxial acceleration sensor4 and the Y axis gyro sensor 5, respectively. It should be appreciated,however, that the present invention is not limited to the embodimentdescribed above. The PND 1 may be configured in such a manner thatmoving average filter processing is applied to the acceleration data ADand the pitch rate data PD in addition to the high-pass filterprocessing and the low-pass filter processing. Alternatively, the PND 1may be configured in such a manner that the high-pass filter processing,the low-pass filter processing, and the moving average filter processingcombined in an arbitrary manner are applied to the acceleration data ADand the pitch rate data PD.

Further, the embodiment of the present invention above has described acase where the velocity V, for example, at the last position P0 iscalculated using the acceleration α_(z) and the pitch rate ω_(y) when itis determined that the velocity V at the last position P0 is excessivelyhigh, the previous value velocity V_(n-1) is used as the velocity V atthe last position P0. It should be appreciated, however, that thepresent invention is not limited to the embodiment described above. Thevelocity calculation portion 22 in the PND 1 may be configured in such amanner that in a case where the velocity V at the last position P0 ishigher than the previous value velocity V_(n-1) by a predeterminedthreshold value or more, it finds a value obtained by adding a valuecomparable to a velocity that the vehicle is presumably able toaccelerate to the previous value velocity V_(n-1) and uses the valuethus found as the velocity V at the last position P0.

Alternatively, the velocity calculation portion 22 in the PND 1 may beconfigured in such a manner that in a case where the velocity V at thelast position P0 is lower than the previous value velocity V_(n-1) by apredetermined threshold or more, it finds a value obtained bysubtracting a value comparable to a velocity that the vehicle ispresumably able to decelerate from the previous value velocity V_(n-1)and uses the value thus found as the velocity V at the last position P0.

Further, the embodiment of the present invention above has described acase where the velocity V is calculated in accordance with Equation (3)above on the basis of the acceleration α_(z) and the pitch rate ω_(y).

It should be appreciated, however, that the present invention is notlimited to the embodiment described above. The control portion 11 in thePND 1 may be configured in such a manner that it compares the velocity Vcalculated in accordance with Equation (3) above on the basis of theacceleration α_(z) and the pitch rate ω_(y) with the GPS velocity V_(g)calculated on the basis of the GPS signals.

In a case where there is an error between the velocity V and the GPSvelocity V_(g), the control portion 11 in the PND 1 calculates acorrection coefficient used to correct the error with the velocity V,for example, so as to minimize the error using a linear function or ahigh-order function, such as a quadratic or higher function, and storesthe correction coefficient in the memory portion 12.

Hence, the velocity calculation portion 22 in the PND 1 calculates thevelocity V in accordance with Equation (3) above on the basis of theacceleration α_(z) and the pitch rate ω_(y) detected by the triaxialacceleration sensor 4 and the Y axis gyro sensor 5, respectively, afterwhich it reads out the correction coefficient from the memory portion 12so as to correct the velocity V by a linear function or a high-orderfunction, such as a quadratic or higher function, using the correctioncoefficient.

As has been described, by preliminarily learning the correctioncoefficient of the velocity V on the basis of the GPS velocity V_(g)calculated on the basis of GPS signals, the PND becomes able to enhancethe calculation accuracy of the velocity V.

When calculating the correction coefficient of the velocity V and theGPS velocity V_(g), the control portion 11 in the PND 1 may divide thevelocity V to a plurality of velocity regions, such as an extremely lowvelocity, a low velocity, a medium velocity, and a high velocity, sothat it calculates a correction coefficient for each of a plurality ofthe velocity regions.

Alternatively, the control portion 11 in the PND 1 may be configured insuch a manner that it calculates a correction coefficient only for apredetermined velocity, for example, a high velocity at 60 [km] per houror higher when calculating a correction coefficient of the velocity Vand the GPS velocity V_(g).

Further, the embodiment of the present invention above has described acase where navigation is performed according to the current positioncalculation processing procedure while the PND 1 receives a supply ofsource power. It should be appreciated, however, that the presentinvention is not limited to the embodiment described above. The PND 1may be configured in such a manner that in a case where the PND 1 isturned OFF when the power supply button (not shown) is depressed by theuser, it stores the current position, the altitude, and the like at apoint in time when the power supply button is depressed into the memoryportion 12. Accordingly, when the user depresses the power supply buttonagain to turn ON the PND 1, it reads out the current position, thealtitude, and the like from the memory portion 12 to resume navigationaccording to the current position calculation processing procedure fromthe current position, the altitude, and the like that have been readout.

Further, the embodiment of the present invention above has described acase where the PND 1 calculates the velocity V while it is held by thecradle 3 mounted on the dashboard of the vehicle. It should beappreciated, however, that the present invention is not limited to theembodiment described above. The PND 1 may be configured in such a mannerthat it sets the velocity V to 0 or maintains the previous valuevelocity V_(n-1) when it acknowledges that it is removed mechanically orelectrically from the cradle 3.

Further, the embodiment of the present invention above has described acase where the PND 1 is used while it is in a transversely mounted stateto be long in the right-left direction. It should be appreciated,however, that the present invention is not limited to the embodimentdescribed above. As is shown in FIG. 38, the PND 1 may be used in alongitudinally mounted state to be long in the length direction. In thiscase, the PND 1 is configured to detect the yaw rate ω_(z) about the Zaxis by the Y axis gyro sensor 5 and to detect the pitch rate ω_(y)about the Y axis by the Z axis gyro sensor 6.

Further, the embodiment of the present invention descried above hasdescribed a case where the triaxial acceleration sensor 4, the Y axisgyro sensor 5, the Z axis gyro sensor 6, and the pressure sensor 7 areprovided inside the PND 1. It should be appreciated, however, that thepresent invention is not limited to the embodiment described above. Itmay be configured in such a manner that the triaxial acceleration sensor4, the Y axis gyro sensor 5, the Z axis gyro sensor 6, and the pressuresensor 7 are provided to the outside of the PND 1.

In addition, the PND 1 may be provided with an adjustment mechanismcapable of adjusting attachment angles of the triaxial accelerationsensor 4, the Y axis gyro sensor 5, the Z axis gyro sensor 6, and thepressure sensor 7, for example, on the side face of the PND 1.

Accordingly, even in a case where the display portion 2 is not providedto be substantially perpendicular to the travel direction of thevehicle, it is possible for the PND 1 to align, for example, therotation axis of the Y axis gyro sensor 5 with the vertical direction ofthe vehicle by allowing the user to make an adjustment via the adjustingmechanism.

Further, in the embodiment of the present invention described above, thevelocity V is determined as being excessively high in a case where thepitch rate ω_(y) corresponding to the pitch rate data PD2 is smallerthan a predetermined threshold value and the acceleration α_(z)corresponding to the acceleration data AD2 and the pitch rate ω_(y)corresponding to the pitch rate PD2 are larger than correspondingpredetermined threshold values. It should be appreciated, however, thatthe present invention is not limited to the embodiment described above.The control portion 11 may be configured in such a manner that itdetermines that the velocity V is excessively high when the velocity Vcalculated by the velocity computation portion 34 takes a value largerthan the previous value velocity V_(n-1) by a predetermined velocity ormore.

In this case, the smoothing and noise removal portion 35 sets thevelocity V to 0 when the velocity V calculated by the velocitycomputation portion 34 takes a value larger than the previous valuevelocity V_(n-1) by a predetermined velocity or more and when theprevious value velocity V_(n-1) is an extremely low velocity, forexample, lower than 10 [km] per hour. Meanwhile, the smoothing and noiseremoval portion 35 uses the previous value velocity V_(n-1) as thevelocity V when the velocity V calculated by the velocity computationportion 34 takes a value larger than the previous value velocity V_(n-1)by a predetermined velocity or more and when the previous value velocityV_(n-1) is, for example, 10 [km] per hour or higher.

Further, the embodiment of the present invention above has described acase where the control portion 11 in the PND 1 performs the currentposition calculation processing procedure in Routine RT1 described aboveaccording to the application program pre-stored in the memory portion12. It should be appreciated, however, that the present invention is notlimited to the embodiment described above. The control portion 11 in thePND 1 may be configured in such a manner that it performs the currentposition calculation processing procedure according to an applicationprogram installed from a storage medium, an application programdownloaded from the Internet, and application programs installed invarious other routes.

Further, the embodiment of the present invention above has described acase where the PND 1 as the velocity calculation device of theembodiment of the present invention is formed of the triaxialacceleration sensor 4 as a vertical direction acceleration detectionportion, the Y axis gyro sensor 5 as a horizontal direction angularvelocity detection portion, and the velocity calculation portion 22 as avelocity calculation portion. It should be appreciated, however, thatthe present invention is not limited to the embodiment described above.The velocity calculation device may be formed of a vertical directionacceleration detection portion, a horizontal direction angular velocitydetection portion, and a velocity calculation portion of other variousconfigurations.

The velocity calculation device, the velocity calculation method, andthe navigation device according to the embodiment of the presentinvention are suitably used as a PND and a stationary navigation devicemounted on a vehicle as well as other various mobile bodies, such as amotor cycle and an electrical train.

The present application contains subject matter related to thatdisclosed in Japanese Priority Patent Application JP 2008-221713 filedin the Japan Patent Office on Aug. 29, 2008, the entire contents ofwhich is hereby incorporated by reference.

It should be understood by those skilled in the art that variousmodifications, combinations, sub-combinations and alterations may occurdepending on design requirements and other factors insofar as they arewithin the scope of the appended claims or the equivalents thereof.

1. (canceled)
 2. A velocity calculation device comprising: a velocitycalculation portion that calculates a velocity in a travel direction ofa vehicle on the basis of an acceleration in a vertical direction thatis detected by a vertical direction acceleration detection portion andgenerated correspondingly to undulation of a road surface on which thevehicle is traveling, and an angular velocity about a horizontal axisthat is detected by a horizontal direction angular velocity detectionportion and generated correspondingly to the undulation of the roadsurface on which the vehicle is traveling, without acquiring informationon traveling from the vehicle.
 3. The velocity calculation deviceaccording to claim 2, wherein: the vertical direction accelerationdetection portion detects accelerations in the vertical directioncontinuously in succession at a predetermined sampling frequency; thehorizontal direction angular velocity detection portion detects angularvelocities about the horizontal axis continuously in succession at thesampling frequency; and the velocity calculation portion calculates thevelocity of the vehicle in succession using the accelerations in thevertical direction in a predetermined sampling number and the angularvelocities about the horizontal axis in the sampling number.
 4. Thevelocity calculation device according to claim 3, wherein: the velocitycalculation portion changes the sampling number by increasing thesampling number when the velocity is at a predetermined velocity orhigher and decreasing the sampling number when the velocity is lowerthan the predetermined velocity.
 5. The velocity calculation deviceaccording to claim 4, wherein: the velocity calculation portion providesa hysteresis characteristic by changing the sampling number between acase where the velocity increases and a case where the velocitydecreases.
 6. The velocity calculation device according to claim 5,wherein: the velocity calculation portion extracts a maximum value and aminimum value from the accelerations in the vertical direction in thesampling number as a maximum acceleration and a minimum acceleration,respectively, extracts a maximum value and a minimum value from theangular velocities about the horizontal axis in the sampling number as amaximum angular velocity and a minimum angular velocity, respectively,and calculates the velocity by dividing a difference between the maximumacceleration and the minimum acceleration by a difference between themaximum angular velocity and the minimum angular velocity.
 7. Thevelocity calculation device according to claim 2, wherein the velocitycalculation portion further includes a low-pass filter that is set witha low-pass cutoff frequency lower than a predetermined frequencygenerated by a cradle when the velocity calculation device is held bythe cradle and filters out a frequency component as high as or higherthan the low-pass cutoff frequency from the acceleration in the verticaldirection and the angular velocity about the horizontal axis.
 8. Thevelocity calculation device according to claim 7, wherein the velocitycalculation portion further includes: a high-pass filter that is setwith a high-pass cutoff frequency lower than a frequency equivalent tothe undulation of the road surface and filters out a frequency componentas high as or lower than the high-pass cutoff frequency from theacceleration in the vertical direction and the angular velocity aboutthe horizontal axis; and a cutoff frequency setting portion that setsthe low-pass cutoff frequency and the high-pass cutoff frequencyaccording to a velocity before.
 9. The velocity calculation deviceaccording to claim 8, wherein the cutoff frequency setting portion setsthe low-pass cutoff frequency and the high-pass cutoff frequency byswitching each of the low-pass cutoff frequency and the high-pass cutofffrequency to a plurality of steps and makes a value of the velocity usedas a threshold value when switching the low-pass cutoff frequency andthe high-pass cutoff frequency different in a case where the velocity isincreasing from the velocity before and in a case where the velocity isdecreasing.
 10. The velocity calculation device according to claim 8,wherein the cutoff frequency setting portion sets each of the low-passcutoff frequency and the high-pass cutoff frequency according to apredetermined function corresponding to the velocity.
 11. The velocitycalculation device according to claim 2, wherein: the velocitycalculation portion sets the velocity to 0 in a case where the velocitytakes a value larger than a last velocity by a predetermined thresholdvalue or more and the last velocity is lower than a predeterminedvelocity, and uses the last velocity as the velocity in a case where thevelocity takes a value larger than the last velocity by thepredetermined threshold value or more and the last velocity is as highas or higher than the predetermined velocity.
 12. The velocitycalculation device according to claim 2, wherein the vertical directionacceleration detection portion is mounted on the vehicle, detects theacceleration in the vertical direction that is generated in the vehicle,and supplies the acceleration in the vertical direction to the velocitycalculation portion.
 13. The velocity calculation device according toclaim 7, wherein: the cradle is fixed to the vehicle; and the verticaldirection acceleration detection portion is mounted on the cradle,detects the acceleration in the vertical direction that is generated inthe vehicle, and supplies the acceleration in the vertical direction tothe velocity calculation portion.
 14. The velocity calculation deviceaccording to claim 2, wherein the horizontal direction angle detectionportion is mounted on the vehicle, detects the angular velocity aboutthe horizontal axis that is generated in the vehicle, and supplies theangular velocity about the horizontal axis to the velocity calculationportion.
 15. The velocity calculation device according to claim 7,wherein: the cradle is fixed to the vehicle; and the horizontaldirection angle detection portion is mounted on the cradle, detects theangular velocity about the horizontal axis that is generated in thevehicle, and supplies the angular velocity about the horizontal axis tothe velocity calculation portion.
 16. A velocity calculation methodcomprising: a velocity calculation step of calculating a velocity in atravel direction of a vehicle on the basis of an acceleration in avertical direction that is detected by a vertical direction accelerationdetection portion and generated correspondingly to undulation of a roadsurface on which the vehicle is traveling, and an angular velocity abouta horizontal axis that is detected by a horizontal direction angularvelocity detection portion and generated correspondingly to theundulation of the road surface on which the vehicle is traveling,without acquiring information on traveling from the vehicle.
 17. Anavigation device comprising: a vertical direction accelerationdetection portion that detects an acceleration in a vertical directiongenerated in a vehicle correspondingly to undulation of a road surface;a horizontal direction angular velocity detection portion that detectsan angular velocity about a horizontal axis orthogonal to a traveldirection of the vehicle generated in the vehicle correspondingly to theundulation of the road surface; a velocity calculation portion thatcalculates a velocity in the travel direction of the vehicle on thebasis of the acceleration in the vertical direction and the angularvelocity about the horizontal axis; a vertical direction angularvelocity detection portion that calculates an angular velocity about avertical axis that is perpendicular to the travel direction; an anglecalculation portion that calculates an angle by which the vehicle hasturned on the basis of the angular velocity about the vertical axis; anda position calculation portion that calculates a position of the vehicleon the basis of the velocity in the travel direction calculated by thevelocity calculation portion and the angle calculated by the anglecalculation portion, without acquiring information on traveling from thevehicle.